Fairness Layer + Rule Engine + Recommendation Engine
Fair decisions, transparent reasoning, and consistency you can validate.
FairMind AI removes identity attributes, applies only merit-based rules, and produces explainable outcomes with fairness validation and improvement guidance.
Identity Fields
Hidden
Bias Proof
Simulated
Alternative Paths
Suggested
Total Audits
0
Stored for auditability
Live
Average Fairness
100%
Based on identity impact simulation
Live
Platform Mode
Running safely in local demo mode. Add Firebase config and SDK wiring for production deployment.
Auth + Firestore are modeled with a safe local demo store for this sandbox build. Firebase configuration is prepared for production wiring.
Run Fairness Audit
Step 1: Select industry and organization. Step 2: Enter merit-based inputs only. Step 3: Run the decision engine.
Identity Hidden from AI
Transparent Outputs
Every result includes why, fairness proof, and next steps.
- ✔ Decision: Approved / Review / Rejected
- ✔ Rule-by-rule pass/fail explanation
- ✔ Merit breakdown and source organization
- ✔ Improvement guidance when gaps exist
Bias Validation
Fairness is tested by simulating hidden identity changes.
- ✔ Male → same result
- ✔ Female → same result
- ✔ Young → same result
- ✔ Old → same result
Smart Recommendations
Better-fit alternatives are suggested without promising approval.
- ✔ Compare with other organizations
- ✔ Show higher chance matches
- ✔ Explain why the alternative fits better
- ✔ Adapted for Banking, HR, and Healthcare